摘要
基于范例知识的诊断是近年来故障诊断领域一个新的研究课题,径向基函数(RBF)是基于相似度的神经元函数。针对基于相似度范例检索存在的不足,将RBF引入范例检索机的设计之中。提出基于RBF的范例检索模型。并通过对模型网络的改进,使检索模型更适合于诊断实际。仿真和实例表明,基于RBF的范例检索方法优于基于BP网检索,是行之有效的方法。
The diagnosis method based on CBR is focused in fau lt diagnosis recently. Radial basis function (RBF)is a kind of neuron functions based on similarity. In allusion to the problem of similarity based case retrie val, the RBF is introduced into design of case retrieval and a RBF based model i s proposed in this paper. By means of improving the model network, the retrieval model becomes more suitable for practical diagnosis. Simulation and practical a pplication show that the RBF based retrieval is better and more effective than B P based one.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2000年第10期18-22,共5页
Journal of Mechanical Engineering
基金
国家"九五"攀登B项目(PD9521908Z1)
国家自然科学基金(59990472)
教育部"现代设计与转子轴承系统"重点实验室开放课题资助项目
关键词
径向基函数
故障诊断
知识系统
检索
神经网络
Radial basis function
Fault diagnosis
Know ledge system
Retrieval
Neural network